AIMC Topic: Image Processing, Computer-Assisted

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A Deep Learning Pipeline for Nucleus Segmentation.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Deep learning is rapidly becoming the technique of choice for automated segmentation of nuclei in biological image analysis workflows. In order to evaluate the feasibility of training nuclear segmentation models on small, custom annotated image datas...

Applications of deep learning in dentistry.

Oral surgery, oral medicine, oral pathology and oral radiology
Over the last few years, translational applications of so-called artificial intelligence in the field of medicine have garnered a significant amount of interest. The present article aims to review existing dental literature that has examined deep lea...

Deep learning in cancer pathology: a new generation of clinical biomarkers.

British journal of cancer
Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers. However, the growing number of these complex biomarkers tends to increase the cost and time for decision-making in routine daily oncology practice; furthermore, bi...

Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI respon...

Joint Local and Global Information Learning With Single Apex Frame Detection for Micro-Expression Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Micro-expressions (MEs) are rapid and subtle facial movements that are difficult to detect and recognize. Most recent works have attempted to recognize MEs with spatial and temporal information from video clips. According to psychological studies, th...

Learning Dual Encoding Model for Adaptive Visual Understanding in Visual Dialogue.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue task involves multiple rounds of dialogues which cover a broad range of visual content that could be related to any objects, relat...

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SS...

Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Detecting human parts at instance-level is an essential prerequisite for the analysis of human keypoints, actions, and attributes. Nonetheless, there is a lack of a large-scale, rich-annotated dataset for human parts detection. We fill in the gap by ...

Detection of cellular micromotion by advanced signal processing.

Scientific reports
Cellular micromotion-a tiny movement of cell membranes on the nm-µm scale-has been proposed as a pathway for inter-cellular signal transduction and as a label-free proxy signal to neural activity. Here we harness several recent approaches of signal p...

Improved automatic detection of herpesvirus secondary envelopment stages in electron microscopy by augmenting training data with synthetic labelled images generated by a generative adversarial network.

Cellular microbiology
Detailed analysis of secondary envelopment of the herpesvirus human cytomegalovirus (HCMV) by transmission electron microscopy (TEM) is crucial for understanding the formation of infectious virions. Here, we present a convolutional neural network (CN...